Results 111 to 120 of about 426 (167)

Formation of self-assembly aggregates in traditional Chinese medicine decoctions and their application in cancer treatments. [PDF]

RSC Adv
Fang C, Wang Y, Pan Z.
europepmc   +1 more source

Diverse material properties and morphology of moth proboscises relates to the feeding habits of some macromoth and other lepidopteran lineages. [PDF]

Interface Focus
Bast EM, Marshall NT, Myers KO, Marsh LW, Hurtado MW, Van Zandt PA, Lehnert MS.   +6 more
europepmc   +1 more source

Prediction model of middle school student performance based on MBSO and MDBO-BP-Adaboost method. [PDF]

Front Big Data
Fang R, Zhou T, Yu B, Li Z, Ma L, Luo T, Zhang Y, Liu X.   +7 more
europepmc   +1 more source

Enhanced cervical precancerous lesions detection and classification using Archimedes Optimization Algorithm with transfer learning. [PDF]

Sci Rep
Allogmani AS, Mohamed RM, Al-Shibly NM, Ragab M.   +3 more
europepmc   +1 more source

Bio-Inspired Strategy for Radiation-Based Thermal Management and Utilization. [PDF]

Adv Sci (Weinh)
Kim HR, Han WB, Heo SY, Go YS, Hwang SW, Song YM.   +5 more
europepmc   +1 more source

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Monarch butterfly optimization

Neural Computing and Applications, 2015
In nature, the eastern North American monarch population is known for its southward migration during the late summer/autumn from the northern USA and southern Canada to Mexico, covering thousands of miles. By simplifying and idealizing the migration of monarch butterflies, a new kind of nature-inspired metaheuristic algorithm, called monarch butterfly ...
Gai-Ge Wang, Suash Deb, Zhihua Cui
exaly   +2 more sources

Monarch butterfly optimization: A comprehensive review

Expert Systems with Applications, 2021
Abstract Swarm intelligence (SI) is the collective behavior of decentralized, self-organized natural or artificial systems. Monarch butterfly optimization (MBO) algorithm is a class of swarm intelligence metaheuristic algorithm inspired by the migration behavior of monarch butterflies. Through the migration operation and butterfly adjusting operation,
Yanhong Feng, Suash Deb, Gai-Ge Wang, Amir H. Alavi   +3 more
openaire   +1 more source

Monarch butterfly optimization algorithm for computed tomography image segmentation

Multimedia Tools and Applications, 2021
In the medical field, image segmentation provides important information for surgical planning and registration, and thus demands accurate segmentation. In order to improve the effectiveness and the threshold accuracy of segmentation, researchers have tended to use a metaheuristic algorithm as the operational algorithm to achieve better exploitation and
O. M. Dorgham, Mohammed Alweshah, M. H. Ryalat, J. Alshaer, M. Khader, S. Alkhalaileh   +5 more
openaire   +1 more source

Harmony-based monarch butterfly optimization algorithm

2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE), 2015
Monarch butterfly optimization (MBO) is a new metaheuristic algorithm mimics the migration of butterflies from northern USA to Mexico. In MBO, there are mainly two processes. In the first process, the algorithm emulates how some of the butterflies move from the current position to the new position by the migration operator.
Mohamed Ghetas, Chan Huah Yong, Putra Sumari   +2 more
openaire   +1 more source

An image segmentation method based on improved Monarch Butterfly Optimization

Iran Journal of Computer Science, 2021
Image segmentation refers to splitting an image into non-identical and significant parts for more accurate classification or interpretation. In general, multi-level thresholding methods are used to find the best threshold levels for image segmentation. Although researchers have proposed different techniques to find the optimal thresholds, this issue is
Babak Masoudi, Hadi S. Aghdasi
openaire   +1 more source